Joint Power and Data Allocation for Energy Harvesting Cognitive Radio Networks

Energy harvesting (EH) cognitive radio (CR) networks have emerged as a promising generation to improve the electricity performance and reliability of Wi-Fi networks. However, because of the unpredictable and intermittent nature of energy harvesting, efficient utilization of the power to be had is a tough hassle. Joint energy and information allocation (JPDA) is a fundamental approach to improving the general overall performance of EH CR networks by intelligently allocating electricity and statistics fees among multiple customers. In this paper, we advocate a novel JPDA scheme for EH CR networks, considering the strength arrival fee, channel situations, and interference from different users. We formulate the problem as a joint optimization of energy and facts allocation, considering strength causality and interference constraints. To resolve this non-convex problem, we employ the alternating optimization method and expand a low-complexity algorithm with assured convergence. Simulation results show that our proposed JPDA scheme notably improves the community throughput and energy efficiency compared to present techniques.